Table (information)

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An example table rendered in a web browser using HTML Table-sample-appearance-default-params-values-01.gif
An example table rendered in a web browser using HTML

A table is an arrangement of information or data, typically in rows and columns, or possibly in a more complex structure. Tables are widely used in communication, research, and data analysis. Tables appear in print media, handwritten notes, computer software, architectural ornamentation, traffic signs, and many other places. The precise conventions and terminology for describing tables vary depending on the context. Further, tables differ significantly in variety, structure, flexibility, notation, representation and use. [1] [2] [3] [4] [5] Information or data conveyed in table form is said to be in tabular format (adjective). In books and technical articles, tables are typically presented apart from the main text in numbered and captioned floating blocks.

Contents

Basic description

A table consists of an ordered arrangement of rows and columns. This is a simplified description of the most basic kind of table. Certain considerations follow from this simplified description:

The elements of a table may be grouped, segmented, or arranged in many different ways, and even nested recursively. Additionally, a table may include metadata, annotations, a header, [6] a footer or other ancillary features. [5]

Simple table

The following illustrates a simple table with three columns and nine rows. The first row is not counted, because it is only used to display the column names. This is called a "header row".

Age table
First nameLast nameAge
TinuElejogun14
JavierZapata28
LilyMcGarrett18
OlatunkboChijiaku22
AdrienneAnthoula22
AxeliaAthanasios22
Jon-KabatZinn22
ThabangMosoa15
RhianEllis12

Multi-dimensional table

An example of a table containing rows with summary information. The summary information consists of subtotals that are combined from previous rows within the same column. Rollup table.png
An example of a table containing rows with summary information. The summary information consists of subtotals that are combined from previous rows within the same column.

The concept of dimension is also a part of basic terminology. [7] Any "simple" table can be represented as a "multi-dimensional" table by normalizing the data values into ordered hierarchies. A common example of such a table is a multiplication table.

Multiplication table
×123
1123
2246
3369

In multi-dimensional tables, each cell in the body of the table (and the value of that cell) relates to the values at the beginnings of the column (i.e. the header), the row, and other structures in more complex tables. This is an injective relation: each combination of the values of the headers row (row 0, for lack of a better term) and the headers column (column 0 for lack of a better term) is related to a unique cell in the table:

The first column often presents information dimension description by which the rest of the table is navigated. This column is called "stub column". Tables may contain three or multiple dimensions and can be classified by the number of dimensions. Multi-dimensional tables may have super-rows - rows that describe additional dimensions for the rows that are presented below that row and are usually grouped in a tree-like structure. This structure is typically visually presented with an appropriate number of white spaces in front of each stub's label. [8]

In literature tables often present numerical values, cumulative statistics, categorical values, and at times parallel descriptions in form of text. [9] They can condense large amount of information to a limited space and therefore they are popular in scientific literature in many fields of study.

Adrien Auzout's "A TABLE of the Apertures of Object-Glasses" from a 1665 article in Philosophical Transactions Philosophical Transactions - Volume 001.djvu
Adrien Auzout's "A TABLE of the Apertures of Object-Glasses" from a 1665 article in Philosophical Transactions

Generic representation

As a communication tool, a table allows a form of generalization of information from an unlimited number of different social or scientific contexts. It provides a familiar way to convey information that might otherwise not be obvious or readily understood.

For example, in the following diagram, two alternate representations of the same information are presented side by side. On the left is the NFPA 704 standard "fire diamond" with example values indicated and on the right is a simple table displaying the same values, along with additional information. Both representations convey essentially the same information, but the tabular representation is arguably more comprehensible to someone who is not familiar with the NFPA 704 standard. The tabular representation may not, however, be ideal for every circumstance (for example because of space limitations, or safety reasons).

Fire diamond
Standard RepresentationTabular Representation
NFPA 704.svgHealth 3: Short exposure could cause serious temporary or residual injury. E.g. chlorine gasFlammability 2: Must be moderately heated or exposed to relatively high ambient temperature before ignition can occur. Flash point between 38 and 93 °C (100 and 200 °F). E.g. diesel fuelInstability 1: Normally stable, but can become unstable at elevated temperatures and pressures. E.g. calciumSpecial hazards (white): no code
3
2
1
Risk levels of hazardous materials in this facility
Health RiskFlammabilityReactivitySpecial
Level 3Level 2Level 1

Specific uses

There are several specific situations in which tables are routinely used as a matter of custom or formal convention.

Publishing

Mathematics

Natural sciences

Information technology

Software applications

Modern software applications give users the ability to generate, format, and edit tables and tabular data for a wide variety of uses, for example:

Software development

Tables have uses in software development for both high-level specification and low-level implementation. Usage in software specification can encompass ad hoc inclusion of simple decision tables in textual documents through to the use of tabular specification methodologies, examples of which include Software Cost Reduction [10] and Statestep. [11] Proponents of tabular techniques, among whom David Parnas is prominent, emphasize their understandability, as well as the quality and cost advantages of a format allowing systematic inspection, [12] while corresponding shortcomings experienced with a graphical notation were cited in motivating the development of at least two tabular approaches. [11] [13]

At a programming level, software may be implemented using constructs generally represented or understood as tabular, whether to store data (perhaps to memoize earlier results), for example, in arrays or hash tables, or control tables determining the flow of program execution in response to various events or inputs.

Databases

Database systems often store data in structures called tables; in which columns are data fields and rows represent data records.

Historical relationship to furniture

In medieval counting houses, the tables were covered with a piece of checkered cloth, to count money. [14] [15] Exchequer is an archaic term for the English institution which accounted for money owed to the monarch. Thus the checkerboard tables of stacks of coins are a concrete realization of this information.[ citation needed ]

See also

Related Research Articles

In computer science, an array is a data structure consisting of a collection of elements, of same memory size, each identified by at least one array index or key. An array is stored such that the position of each element can be computed from its index tuple by a mathematical formula. The simplest type of data structure is a linear array, also called one-dimensional array.

A relational database (RDB) is a database based on the relational model of data, as proposed by E. F. Codd in 1970. A database management system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems are equipped with the option of using SQL for querying and updating the database.

The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database.

<span class="mw-page-title-main">Spreadsheet</span> Computer application for organization, analysis, and storage of data in tabular form

A spreadsheet is a computer application for computation, organization, analysis and storage of data in tabular form. Spreadsheets were developed as computerized analogs of paper accounting worksheets. The program operates on data entered in cells of a table. Each cell may contain either numeric or text data, or the results of formulas that automatically calculate and display a value based on the contents of other cells. The term spreadsheet may also refer to one such electronic document.

Flexible Image Transport System (FITS) is an open standard defining a digital file format useful for storage, transmission and processing of data: formatted as multi-dimensional arrays, or tables. FITS is the most commonly used digital file format in astronomy. The FITS standard was designed specifically for astronomical data, and includes provisions such as describing photometric and spatial calibration information, together with image origin metadata.

<span class="mw-page-title-main">Comma-separated values</span> File format used to store data

Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the CSV file. If the field delimiter itself may appear within a field, fields can be surrounded with quotation marks.

<span class="mw-page-title-main">Graph (abstract data type)</span> Abstract data type in computer science

In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics.

<span class="mw-page-title-main">Flat-file database</span> Database stored as an ordinary unstructured file

A flat-file database is a database stored in a file called a flat file. Records follow a uniform format, and there are no structures for indexing or recognizing relationships between records. The file is simple. A flat file can be a plain text file, or a binary file. Relationships can be inferred from the data in the database, but the database format itself does not make those relationships explicit.

<span class="mw-page-title-main">Zachman Framework</span> Structure for enterprise architecture

The Zachman Framework is an enterprise ontology and is a fundamental structure for enterprise architecture which provides a formal and structured way of viewing and defining an enterprise. The ontology is a two dimensional classification schema that reflects the intersection between two historical classifications. The first are primitive interrogatives: What, How, When, Who, Where, and Why. The second is derived from the philosophical concept of reification, the transformation of an abstract idea into an instantiation. The Zachman Framework reification transformations are: identification, definition, representation, specification, configuration and instantiation.

A table is a collection of related data held in a table format within a database. It consists of columns and rows.

A pivot table is a table of values which are aggregations of groups of individual values from a more extensive table within one or more discrete categories. The aggregations or summaries of the groups of the individual terms might include sums, averages, counts, or other statistics. A pivot table is the outcome of the statistical processing of tabularized raw data and can be used for decision-making.

Data drilling refers to any of various operations and transformations on tabular, relational, and multidimensional data. The term has widespread use in various contexts, but is primarily associated with specialized software designed specifically for data analysis.

Data Interchange Format (.dif) is a text file format used to import/export single spreadsheets between spreadsheet programs.

<span class="mw-page-title-main">Dimension (data warehouse)</span> Structure that categorizes facts and measures in a data warehouse

A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time.

Data cleansing or data cleaning is the process of detecting and correcting corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting or a data quality firewall.

<span class="mw-page-title-main">Database model</span> Type of data model

A database model is a type of data model that determines the logical structure of a database. It fundamentally determines in which manner data can be stored, organized and manipulated. The most popular example of a database model is the relational model, which uses a table-based format.

<span class="mw-page-title-main">Numbers (spreadsheet)</span> Spreadsheet application by Apple Inc.

Numbers is a spreadsheet application developed by Apple Inc. as part of the iWork productivity suite alongside Keynote and Pages. Numbers is available for iOS and macOS High Sierra or newer. Numbers 1.0 on Mac OS X was announced on August 7, 2007, making it the newest application in the iWork suite. The iPad version was released on January 27, 2010. The app was later updated to support iPhone and iPod Touch.

In mathematics, an orthogonal array is a "table" (array) whose entries come from a fixed finite set of symbols, arranged in such a way that there is an integer t so that for every selection of t columns of the table, all ordered t-tuples of the symbols, formed by taking the entries in each row restricted to these columns, appear the same number of times. The number t is called the strength of the orthogonal array. Here are two examples:

A geographic data model, geospatial data model, or simply data model in the context of geographic information systems, is a mathematical and digital structure for representing phenomena over the Earth. Generally, such data models represent various aspects of these phenomena by means of geographic data, including spatial locations, attributes, change over time, and identity. For example, the vector data model represents geography as collections of points, lines, and polygons, and the raster data model represent geography as cell matrices that store numeric values. Data models are implemented throughout the GIS ecosystem, including the software tools for data management and spatial analysis, data stored in a variety of GIS file formats, specifications and standards, and specific designs for GIS installations.

The following is provided as an overview of and topical guide to databases:

References

  1. ↑ Fink, Arlene (2005). How to Conduct Surveys. Thousand Oaks: Sage Publications. ISBN   1-4129-1423-X.
  2. ↑ McNabb, David (2002). Research Methods in Public Administration and Nonprofit Management. Armonk: M.E. Sharpe. ISBN   0-7656-0957-6.
  3. ↑ Morgan, George (2004). Spss for Introductory Statistics . Hillsdale: Lawrence Erlbaum. ISBN   0-8058-4789-8.
  4. ↑ Robey, David (2000). Sound and Structure in the Divine Comedy. Oxford Oxfordshire: Oxford University Press. ISBN   0-19-818498-0.
  5. 1 2 Zielinski, Krzysztof (2006). Software Engineering: Evolution and Emerging Technologies. Amsterdam: IOS Press. ISBN   1-58603-559-2.
  6. ↑ see e.g., Page header or Header (computing)
  7. ↑ The concept of "dimension" is often applied to tables in different contexts and with different meanings. For example, what is described as a "Simple Table" in this article is alternatively described as a "two dimensional array". This is distinct from "multi-dimensional table" as presented in this article.
  8. ↑ Milosevic N, Gregson C, Hernandez R, Nenadic G (June 2016). "Disentangling the Structure of Tables in Scientific Literature" (PDF). Proceedings of 21st International Conference on Applications of Natural Language to Information Systems (NLDB 2016). Lecture Notes in Computer Science. 9612: 162–174. doi:10.1007/978-3-319-41754-7_14. ISBN   978-3-319-41753-0. S2CID   19538141.
  9. ↑ Milosevic N, Gregson C, Hernandez R, Nenadic G (February 2019). "A framework for information extraction from tables in biomedical literature". International Journal on Document Analysis and Recognition. 22 (1): 55–78. arXiv: 1902.10031 . doi:10.1007/s10032-019-00317-0. S2CID   62880746.
  10. ↑ Heitmeyer, Constance L. (2002). "Software Cost Reduction". Washington D.C.: Naval Research Laboratory. Archived from the original on March 12, 2012.
  11. 1 2 Breen, Michael (2005). "Experience of using a lightweight formal specification method for a commercial embedded system product line" (PDF). Requirements Engineering Journal. 10 (2): 161–172. doi:10.1007/s00766-004-0209-1. S2CID   16928695.
  12. ↑ Janicki, Ryszard; Parnas, David Lorge; Zucker, Jeffery (1997). "Tabular representations in relational documents". In Brink, C.; Kahl, W.; Schmidt, G. (eds.). Relational Methods in Computer Science. Springer Verlag. ISBN   3-211-82971-7.
  13. ↑ Leveson, Nancy G.; Heimdahl, Mats P. E.; Reese, Jon Damon (1999). "Designing Specification Languages for Process-Control Systems: Lessons Learned and Steps to the Future". Seventh ACM SIGSOFT Symposium on the Foundations on Software Engineering (PDF). Lecture Notes in Computer Science. Vol. 1687. pp. 127–146. doi:10.1007/3-540-48166-4_9. hdl:11299/217294. ISBN   978-3-540-66538-0.
  14. ↑ Baxter, W. T. (1989). "Early Accounting: The Tally and Checkerboard". The Accounting Historians Journal. 16 (2): 43–83. doi:10.2308/0148-4184.16.2.43. ISSN   0148-4184. JSTOR   40697984.
  15. ↑ "The Exchequer: a chequered history? - History of government". history.blog.gov.uk. 14 August 2013. Retrieved 2023-04-13.
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